A Predictive Model for the Bioaccumulation of Okadaic Acid in Mytilus galloprovincialis Farmed in the Northern Adriatic Sea: A Tool to Reduce Product Losses and Improve Mussel Farming Sustainability

Fabrizio Capoccioni, Laura Bille, Federica Colombo, Lidia Contiero, Arianna Martini, Carmine Mattia, Riccardo Napolitano, Nicolò Tonachella, Marica Toson and Domitilla Pulcini ()
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Fabrizio Capoccioni: Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Centro di Ricerca Zootecnia e Acquacoltura, Via Salaria 31, 00015 Monterotondo, Italy
Laura Bille: Istituto Zooprofilattico Sperimentale Delle Venezie, Viale dell’Università 10, 35020 Legnaro, Italy
Federica Colombo: ColomboSky S.r.l., Via Giacomo Peroni 442/444, 00131 Roma, Italy
Lidia Contiero: Istituto Zooprofilattico Sperimentale Delle Venezie, Viale dell’Università 10, 35020 Legnaro, Italy
Arianna Martini: Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Centro di Ricerca Zootecnia e Acquacoltura, Via Salaria 31, 00015 Monterotondo, Italy
Carmine Mattia: ColomboSky S.r.l., Via Giacomo Peroni 442/444, 00131 Roma, Italy
Riccardo Napolitano: Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Centro di Ricerca Zootecnia e Acquacoltura, Via Salaria 31, 00015 Monterotondo, Italy
Nicolò Tonachella: Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Centro di Ricerca Zootecnia e Acquacoltura, Via Salaria 31, 00015 Monterotondo, Italy
Marica Toson: Istituto Zooprofilattico Sperimentale Delle Venezie, Viale dell’Università 10, 35020 Legnaro, Italy
Domitilla Pulcini: Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Centro di Ricerca Zootecnia e Acquacoltura, Via Salaria 31, 00015 Monterotondo, Italy

Sustainability, 2023, vol. 15, issue 11, 1-14

Abstract: Over the last decades, harmful dinoflagellate ( Dinophysis spp.) blooms have increased in frequency, duration, and severity in the Mediterranean Sea. Farmed bivalves, by ingesting large amounts of phytoplankton, can become unsafe for human consumption due to the bioaccumulation of okadaic acid (OA), causing Diarrhetic Shellfish Poisoning (DSP). Whenever the OA concentration in shellfish farmed in a specific area exceeds the established legal limit (160 μg·kg −1 of OA equivalents), harvesting activities are compulsorily suspended. This study aimed at developing a machine learning (ML) predictive model for OA bioaccumulation in Mediterranean mussels ( Mytilus galloprovincialis ) farmed in the coastal area off the Po River Delta (Veneto, Italy), based on oceanographic data measured through remote sensing and data deriving from the monitoring activities performed by official veterinarian authorities to verify the bioaccumulation of OA in the shellfish production sites. LightGBM was used as an ML algorithm. The results of the classification algorithm on the test set showed an accuracy of 82%. Further analyses showed that false negatives were mainly associated with relatively low levels of toxins (<100 μg·kg −1 ), since the algorithm tended to classify low concentrations of OA as negative samples, while true positives had higher mean values of toxins (139 μg·kg −1 ). The results of the model could be used to build up an online early warning system made available to shellfish farmers of the study area, aimed at increasing the economic and environmental sustainability of these production activities and reducing the risk of massive product losses.

Keywords: harmful algal blooms; LightGBM algorithm; machine learning; okadaic acid; remote sensing; shellfish (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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